package Lab5;
/**
 * 实验 5 
 * 问题 2. 编程实现对输入文件的排序。
 */

import java.io.IOException;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.Mapper;
import org.apache.hadoop.mapreduce.Partitioner;
import org.apache.hadoop.mapreduce.Reducer;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
import org.apache.hadoop.util.GenericOptionsParser;

public class Lab5P02 {
    /**
     * @param args
     * 输入多个文件，每个文件中的每行内容均为一个整数
     * 输出到一个新的文件中，输出的数据格式为每行两个整数，第一个数字为第二个整数的排序位次，第二个整数为原待排列的整数
     */
    //map函数读取输入中的value，将其转化成IntWritable类型，最后作为输出key
    public static class Map extends Mapper<Object, Text, IntWritable, IntWritable>{
 
        private static IntWritable data = new IntWritable();
        public void map(Object key, Text value, Context context) throws IOException,InterruptedException{
            String text = value.toString();
            data.set(Integer.parseInt(text));
            context.write(data, new IntWritable(1));
        }
    }
 
    //reduce函数将map输入的key复制到输出的value上，然后根据输入的value-list中元素的个数决定key的输出次数,定义一个全局变量line_num来代表key的位次
    public static class Reduce extends Reducer<IntWritable, IntWritable, IntWritable, IntWritable>{
        private static IntWritable line_num = new IntWritable(1);
        public void reduce(IntWritable key, Iterable<IntWritable> values, Context context) throws IOException,InterruptedException{
            for(IntWritable val : values){
                context.write(line_num, key);
                line_num = new IntWritable(line_num.get() + 1);
            }
        }
    }
 
    //自定义Partition函数，此函数根据输入数据的最大值和MapReduce框架中Partition的数量获取将输入数据按照大小分块的边界，然后根据输入数值和边界的关系返回对应的Partiton ID
    public static class Partition extends Partitioner<IntWritable, IntWritable>{
        public int getPartition(IntWritable key, IntWritable value, int num_Partition){
            int Maxnumber = 65223;//int型的最大数值
            int bound = Maxnumber/num_Partition+1;
            int keynumber = key.get();
            for (int i = 0; i<num_Partition; i++){
                if(keynumber<bound * (i+1) && keynumber>=bound * i){
                    return i;
                }
            }
            return -1;
        }
    }
 
    public static void main(String[] args) throws Exception{
        // TODO Auto-generated method stub
        Configuration conf = new Configuration();
        conf.set("fs.default.name","hdfs://localhost:9000");
        String[] otherArgs = new String[]{"input","output"}; /* 直接设置输入参数 */
        if (otherArgs.length != 2) {
            System.err.println("Usage: wordcount <in><out>");
            System.exit(2);
        }
        Job job = Job.getInstance(conf,"Merge and sort");
        job.setJarByClass(Lab5P02.class);
        job.setMapperClass(Map.class);
        job.setReducerClass(Reduce.class);
        job.setPartitionerClass(Partition.class);
        job.setOutputKeyClass(IntWritable.class);
        job.setOutputValueClass(IntWritable.class);
        FileInputFormat.addInputPath(job, new Path(otherArgs[0]));
        FileOutputFormat.setOutputPath(job, new Path(otherArgs[1]));
        System.exit(job.waitForCompletion(true) ? 0 : 1);
    }
}
